The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach

In a typical location–allocation problem, customer demand data are often aggregated according to some arbitrary spatial points (e.g. population centers) or boundaries (e.g. census districts). Since such points or boundaries do not represent true sources of customer demands, allocation of aggregated customers to distribution centers can lead to underutilization of distribution centers and deterioration of customer services. In an effort to design a supply chain network that maintains the best balance of transportation cost and customer service, this paper proposes a new model based on naïve balanced star spanning forest formulation. This model goes beyond traditional mathematical programming by incorporating a genetic algorithm that is proven to be effective in dealing with the NP-hard problem.